ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information

被引:9
作者
Abad, Zahra Shakeri Hossein [1 ]
Gervasi, Vincenzo [2 ]
Zowghi, Didar [3 ]
Barker, Ken [1 ]
机构
[1] Univ Calgary, Dept Comp Sci, Calgary, AB, Canada
[2] Univ Pisa, Dept Comp Sci, Pisa, Italy
[3] Univ Technol Sydney, Sch Software, Sydney, NSW, Australia
来源
2018 5TH INTERNATIONAL WORKSHOP ON ARTIFICIAL INTELLIGENCE FOR REQUIREMENTS ENGINEERING (AIRE 2018) | 2018年
关键词
Requirements elicitation; Natural language processing; Tool support; Dynamic information extraction; ELICITATION; LANGUAGE; KNOWLEDGE;
D O I
10.1109/AIRE.2018.00007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Requirements elicitation requires extensive knowledge and deep understanding of the problem domain where the final system will be situated. However, in many software development projects, analysts are required to elicit the requirements from an unfamiliar domain, which often causes communication barriers between analysts and stakeholders. In this paper, we propose a requirements ELICitation Aid tool (ELICA) to help analysts better understand the target application domain by dynamic extraction and labeling of requirements-relevant knowledge. To extract the relevant terms, we leverage the flexibility and power of Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural language processing tasks. In addition to the information conveyed through text, ELICA captures and processes non-linguistic information about the intention of speakers such as their confidence level, analytical tone, and emotions. The extracted information is made available to the analysts as a set of labeled snippets with highlighted relevant terms which can also be exported as an artifact of the Requirements Engineering (RE) process. The application and usefulness of ELICA are demonstrated through a case study. This study shows how pre-existing relevant information about the application domain and the information captured during an elicitation meeting, such as the conversation and stakeholders' intentions, can be captured and used to support analysts achieving their tasks.
引用
收藏
页码:8 / 14
页数:7
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